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Estimation of ion competition via correlated responsivity offset in linear ion trap mass spectrometry analysis: theory and practical use in the analysis of cyanobacterial hepatotoxin microcystin-LR in extracts of food additives
J. Urban, P. Hrouzek, D. Stys, H. Martens,
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't
NLK
Free Medical Journals
from 2013
PubMed Central
from 2013
Europe PubMed Central
from 2013
ProQuest Central
from 2013
Open Access Digital Library
from 2001-01-01
Open Access Digital Library
from 2012-12-04
Open Access Digital Library
from 2013-01-01
CINAHL Plus with Full Text (EBSCOhost)
from 2013-01-01
Medline Complete (EBSCOhost)
from 2013-01-01
Health & Medicine (ProQuest)
from 2013
Wiley-Blackwell Open Access Titles
from 2001
ROAD: Directory of Open Access Scholarly Resources
from 2013
PubMed
23586036
DOI
10.1155/2013/414631
Knihovny.cz E-resources
- MeSH
- Peptides, Cyclic analysis MeSH
- Mass Spectrometry * MeSH
- Ions chemistry isolation & purification MeSH
- Humans MeSH
- Microcystins isolation & purification MeSH
- Food Additives analysis MeSH
- Regression Analysis MeSH
- Cyanobacteria isolation & purification MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Responsivity is a conversion qualification of a measurement device given by the functional dependence between the input and output quantities. A concentration-response-dependent calibration curve represents the most simple experiment for the measurement of responsivity in mass spectrometry. The cyanobacterial hepatotoxin microcystin-LR content in complex biological matrices of food additives was chosen as a model example of a typical problem. The calibration curves for pure microcystin and its mixtures with extracts of green alga and fish meat were reconstructed from the series of measurement. A novel approach for the quantitative estimation of ion competition in ESI is proposed in this paper. We define the correlated responsivity offset in the intensity values using the approximation of minimal correlation given by the matrix to the target mass values of the analyte. The estimation of the matrix influence enables the approximation of the position of a priori unknown responsivity and was easily evaluated using a simple algorithm. The method itself is directly derived from the basic attributes of the theory of measurements. There is sufficient agreement between the theoretical and experimental values. However, some theoretical issues are discussed to avoid misinterpretations and excessive expectations.
References provided by Crossref.org
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